RESEARCH PAPER
A novel approach to optimize the maintenance strategies: a case in the hydroelectric power plant
1
Industrial Engineering Department, Kırıkkale University, 71451, Kırıkkale, Turkey
Publication date: 2021-06-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(2):324-337
HIGHLIGHTS
- The maintenance strategy optimization model, which takes into account the wear rate, has been proposed.
- AHP, COPRAS and integer programming methods are used.
- The problem is addressed in the system dimension.
- A feasible model has been proposed.
KEYWORDS
maintenance managementmaintenance strategy optimizationmulti-criteria decision makingAHPCOPRASinteger programming
ABSTRACT
Countries need to develop sustainable energy policies based on the principles of environmental sensitivity, reliability, efficiency, economy and uninterrupted service and to maintain
their energy supply in order to increase their global competitiveness. In addition to this
impact of sustainable energy supply on the global world, maintenance processes in power
plants require high costs due to allocated time, materials and labor, and generation loss.
Thus, the maintenance needs to be managed within a system. This makes analytical and feasible maintenance planning a necessity in power plants. In this context, this study focuses on
maintenance strategy optimization which is the first phase of maintenance planning for one
of the large-scale hydroelectric power plants with a direct effect on Turkey's energy supply
security with its one fifth share in total generation. In this study, a new model is proposed for
the maintenance strategy optimization problem considering the multi-objective and multicriteria structure of hydroelectric power plants with hundreds of complex equipment and the
direct effect of these equipment on uninterrupted and cost-effective electricity generation.
In the model, two multi-criteria decision-making methods, AHP and COPRAS methods,
are integrated with integer programming method and optimal maintenance strategies are
obtained for 571 equipment.
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